title: Risk factors for late-life cognitive decline and variation with age and sex in the Sydney Memory and Ageing Study.
abstract: BACKGROUND
  An aging population brings increasing burdens and costs to individuals and society arising from late-life cognitive decline, the causes of which are unclear. We aimed to identify factors predicting late-life cognitive decline.
  
  
  METHODS
  Participants were 889 community-dwelling 70-90-year-olds from the Sydney Memory and Ageing Study with comprehensive neuropsychological assessments at baseline and a 2-year follow-up and initially without dementia. Cognitive decline was considered as incident mild cognitive impairment (MCI) or dementia, as well as decreases in attention/processing speed, executive function, memory, and global cognition. Associations with baseline demographic, lifestyle, health and medical factors were determined.
  
  
  RESULTS
  All cognitive measures showed decline and 14% of participants developed incident MCI or dementia. Across all participants, risk factors for decline included older age and poorer smelling ability most prominently, but also more education, history of depression, being male, higher homocysteine, coronary artery disease, arthritis, low health status, and stroke. Protective factors included marriage, kidney disease, and antidepressant use. For some of these factors the association varied with age or differed between men and women. Additional risk and protective factors that were strictly age- and/or sex-dependent were also identified. We found salient population attributable risks (8.7-49.5%) for older age, being male or unmarried, poor smelling ability, coronary artery disease, arthritis, stroke, and high homocysteine.
  
  
  CONCLUSIONS
  Preventing or treating conditions typically associated with aging might reduce population-wide late-life cognitive decline. Interventions tailored to particular age and sex groups may offer further benefits.
authors.affiliation: Centre for Healthy Brain Ageing, School of Psychiatry, Faculty of Medicine, University of New South Wales, Australia.
authors.forename: Darren M
authors.initials: DM
authors.lastname: Lipnicki
authors.forename: Perminder S
authors.initials: PS
authors.lastname: Sachdev
authors.forename: John
authors.initials: J
authors.lastname: Crawford
authors.forename: Simone
authors.initials: S
authors.lastname: Reppermund
authors.forename: Nicole A
authors.initials: NA
authors.lastname: Kochan
authors.forename: Julian N
authors.initials: JN
authors.lastname: Trollor
authors.forename: Brian
authors.initials: B
authors.lastname: Draper
authors.forename: Melissa J
authors.initials: MJ
authors.lastname: Slavin
authors.forename: Kristan
authors.initials: K
authors.lastname: Kang
authors.forename: Ora
authors.initials: O
authors.lastname: Lux
authors.forename: Karen A
authors.initials: KA
authors.lastname: Mather
authors.forename: Henry
authors.initials: H
authors.lastname: Brodaty
mesh_terms: D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D003071:Cognition; D060825:Cognitive Dysfunction / Q000453:epidemiology / Q000209:etiology* / Q000523:psychology; D062665:Epidemiological Monitoring; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D015999:Multivariate Analysis; D009517:New South Wales; D016017:Odds Ratio; D012307:Risk Factors; D017678:Sex Distribution